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Entropy 2019, 21(3), 230; https://doi.org/10.3390/e21030230

Asynchronous Control of P300-Based Brain–Computer Interfaces Using Sample Entropy

Biomedical Engineering Group, E.T.S.I. Telecomunicación, University of Valladolid, Paseo de Belén 15, 47011 Valladolid, Spain
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Received: 4 January 2019 / Revised: 15 February 2019 / Accepted: 25 February 2019 / Published: 27 February 2019
(This article belongs to the Special Issue The 20th Anniversary of Entropy - Approximate and Sample Entropy)
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Abstract

Brain–computer interfaces (BCI) have traditionally worked using synchronous paradigms. In recent years, much effort has been put into reaching asynchronous management, providing users with the ability to decide when a command should be selected. However, to the best of our knowledge, entropy metrics have not yet been explored. The present study has a twofold purpose: (i) to characterize both control and non-control states by examining the regularity of electroencephalography (EEG) signals; and (ii) to assess the efficacy of a scaled version of the sample entropy algorithm to provide asynchronous control for BCI systems. Ten healthy subjects participated in the study, who were asked to spell words through a visual oddball-based paradigm, attending (i.e., control) and ignoring (i.e., non-control) the stimuli. An optimization stage was performed for determining a common combination of hyperparameters for all subjects. Afterwards, these values were used to discern between both states using a linear classifier. Results show that control signals are more complex and irregular than non-control ones, reaching an average accuracy of 94 . 40 % in classification. In conclusion, the present study demonstrates that the proposed framework is useful in monitoring the attention of a user, and granting the asynchrony of the BCI system. View Full-Text
Keywords: sample entropy; multiscale entropy; brain–computer interfaces; asynchrony; event-related potentials; P300-evoked potentials; oddball paradigm sample entropy; multiscale entropy; brain–computer interfaces; asynchrony; event-related potentials; P300-evoked potentials; oddball paradigm
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Martínez-Cagigal, V.; Santamaría-Vázquez, E.; Hornero, R. Asynchronous Control of P300-Based Brain–Computer Interfaces Using Sample Entropy. Entropy 2019, 21, 230.

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